Various non-pharmaceutical interventions were adopted by countries worldwide in the fight against the COVID-19 pandemic with adverse socioeconomic side effects, which raises the question about their differential effectiveness. We estimate the average dynamic effect of each intervention on the incidence of COVID-19 and on people’s whereabouts by developing a statistical model that accounts for the contemporaneous adoption of multiple interventions. Using daily data from 175 countries, we show that, even after controlling for other concurrent lockdown policies, cancelling public events, imposing restrictions on private gatherings and closing schools and workplaces had significant effects on reducing COVID-19 infections. Restrictions on internal movement and public transport had no effects because the aforementioned policies, imposed earlier on average, had already de facto reduced human mobility. International travel restrictions, although imposed early, had a short-lived effect failing to prevent the epidemic from turning into a pandemic because they were less stringent. We interpret the impact of each intervention on containing the pandemic using a conceptual framework which relies on their effects on human mobility behaviors in a manner consistent with time-use and epidemiological factors.

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The current economic crisis requires fast information to predict economic behavior early, which is difficult at times of structural changes. This paper suggests an innovative new method of using data on internet activity for that purpose. It demonstrates strong correlations between keyword searches and unemployment rates using monthly German data and exhibits a strong potential for the method used.

The current economic crisis requires fast information to predict economic behavior early, which is difficult at times of structural changes. This paper suggests an innovative new method of using data on internet activity for that purpose. It demonstrates strong correlations between keyword searches and unemployment rates using monthly German data and exhibits a strong potential for the method used.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit organization supported by Deutsche Post Foundation. The center is associated with the University of Bonn and offers a stimulating research environment through its international network, workshops and conferences, data service, project support, research visits and doctoral program. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. Terms of use: Documents inIZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author. This paper advocates the use of Internet data for social sciences with a special focus on human resources issues. It discusses the potentials and challenges of Internet data for social sciences and presents a selection of the relevant literature to establish the wide spectrum of topics, which can be reached. Such data represent a large and increasing part of everyday life, which cannot be measured otherwise. They are timely, perhaps even daily following the factual process, they typically involve large numbers of observations, and they allow for flexible conceptual forms and experimental settings. Internet data can successfully be applied to a very wide range of human resource issues including forecasting (e.g. of unemployment, consumption goods, tourism, festival winners and the like), nowcasting (obtaining relevant information much earlier than through traditional data collection techniques), detecting health issues and well-being (e.g. flu, malaise and ill-being during economic crises), documenting the matching process in various parts of individual life (e.g. jobs, partnership, shopping), and measuring complex processes where traditional data have known deficits (e.g. international migration, collective bargaining agreements in developing countries). Major problems in data analysis are still unsolved and more research on data reliability is needed. Current research is highly original but also exploratory and premature. Our article reviews the current attempts in the literature to incorporate Internet d...